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Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are neurodevelopmental conditions which impact on a significant number of children and adults. Currently, the diagnosis of such disorders is done by experts who employ standard questionnaires and look for certain behavioural markers through manual observation. Such methods for their diagnosis are not only subjective,...
This paper presents GPU parallelization for a computational fluid dynamics solver which works on a mesh consisting of polyhedral cells, where each cell has an arbitrary number of faces and each face has an arbitrary number of vertices. The parallelization is achieved using NVIDIAs compute unified device architecture (CUDA). The developed code specifically targets performance improvement on NVIDIA...
Spontaneous facial expression recognition under uncontrolled conditions is a hard task. It depends on multiple factors including shape, appearance and dynamics of the facial features, all of which are adversely affected by environmental noise and low intensity signals typical of such conditions. In this work, we present a novel approach to Facial Action Unit detection using a combination of Convolutional...
Current approaches to automatic analysis of facial action units (AU) can differ in the way the face appearance is represented. Some works represent the whole face, dividing the bounding box region in a regular grid, and applying a feature descriptor to each subpatch. Alternatively, it is also common to consider local patches around the facial landmarks, and apply appearance descriptors to each of...
Facial landmark detection in real world images is a difficult problem due to the high degree of variation in pose, facial expression and illumination, and the presence of occlusions and background clutter. We propose a system that addresses the problem of head pose and facial expressions in a guided unsupervised learning approach to establish mode specific models. To detect 68 fiducial facial points...
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